Background Obesity and its cardiovascular complications are extremely common medical problems, but evidence on how to accomplish weight loss in clinical practice is sparse. Methods We conducted a randomized, controlled trial to examine the effects of two behavioral weight-loss interventions in 415 obese patients with at least one cardiovascular risk factor. Participants were recruited from six primary care practices; 63.6% were women, 41.0% were black, and the mean age was 54.0 years. One intervention provided patients with weight-loss support remotely — through the telephone, a study-specific Web site, and e-mail. The other intervention provided in-person support during group and individual sessions, along with the three remote means of support. There was also a control group in which weight loss was self-directed. Outcomes were compared between each intervention group and the control group and between the two intervention groups. For both interventions, primary care providers reinforced participation at routinely scheduled visits. The trial duration was 24 months. Results At baseline, the mean body-mass index (the weight in kilograms divided by the square of the height in meters) for all participants was 36.6, and the mean weight was 103.8 kg. At 24 months, the mean change in weight from baseline was −0.8 kg in the control group, −4.6 kg in the group receiving remote support only (P<0.001 for the comparison with the control group), and −5.1 kg in the group receiving in-person support (P<0.001 for the comparison with the control group). The percentage of participants who lost 5% or more of their initial weight was 18.8% in the control group, 38.2% in the group receiving remote support only, and 41.4% in the group receiving in-person support. The change in weight from baseline did not differ significantly between the two intervention groups. Conclusions In two behavioral interventions, one delivered with in-person support and the other delivered remotely, without face-to-face contact between participants and weight-loss coaches, obese patients achieved and sustained clinically significant weight loss over a period of 24 months. (Funded by the National Heart, Lung, and Blood Institute and others; ClinicalTrials.gov number, NCT00783315.)

Background Cigarette smoking is an established predictor of incident type 2 diabetes mellitus, but the effects of smoking cessation on diabetes risk are unknown. Objective To test the hypothesis that smoking cessation increases diabetes risk in the short term, possibly due to cessation-related weight gain. Design Prospective cohort study. Setting The Atherosclerosis Risk in Communities (ARIC) study. Patients 10,892 middle-aged adults who initially did not have diabetes in 1987 to 1989. Measurements We assessed smoking by interview at baseline and at subsequent follow-ups. Incident diabetes was ascertained by fasting glucose assays through 1998 and self-report of physician diagnosis or use of diabetes medications through 2004. Results During 9 years of follow-up, 1,254 adults developed type 2 diabetes. Compared with adults who never smoked, the adjusted hazard ratio of incident diabetes in the highest tertile of pack-years was 1.42 (95% CI, 1.20 to 1.67). In the first 3 years of follow-up, 380 adults quit smoking. After adjustment for age, race, sex, education, adiposity, physical activity, lipids, blood pressure, and ARIC center, compared with adults who never smoked the hazard ratio of diabetes among former smokers, new quitters, and continuing smokers were 1.22 (CI, 0.99 to 1.50), 1.73 (CI, 1.19 to 2.53), and 1.31 (CI, 1.04 to 1.65), respectively. Further adjustment for weight change and leukocyte count attenuated these risks substantially. In an analysis of long-term risk after quitting, the highest risk occurred in the first 3 years (hazard ratio, 1.91 [CI, 1.19 to 3.05]), then gradually decreased to 0 at 12 years. Limitation Residual confounding is possible even with the most meticulous adjustment for established diabetes risk factors. Conclusion Cigarette smoking predicts incident type 2 diabetes, but smoking cessation leads to higher short-term risk. For smokers at risk for diabetes, smoking cessation should be coupled with strategies for diabetes prevention and early detection.

Several lines of evidence support the notion that elevated blood viscosity may predispose to insulin resistance and type 2 diabetes mellitus by limiting delivery of glucose, insulin, and oxygen to metabolically active tissues. To test this hypothesis, the authors analyzed longitudinal data on 12,881 initially nondiabetic adults, aged 45–64 years, who were participants in the Atherosclerosis Risk in Communities (ARIC) Study (1987–1998). Whole blood viscosity was estimated by using a validated formula based on hematocrit and total plasma proteins at baseline. At baseline, estimated blood viscosity was independently associated with several features of the metabolic syndrome. In models adjusted simultaneously for known predictors of diabetes, estimated whole blood viscosity and hematocrit predicted incident type 2 diabetes mellitus in a graded fashion (Ptrend (linear) < 0.001): Compared with their counterparts in the lowest quartiles, adults in the highest quartile of blood viscosity (hazard ratio = 1.68, 95% confidence interval: 1.53, 1.84) and hematocrit (hazard ratio = 1.63, 95% confidence interval: 1.49, 1.79) were over 60% more likely to develop diabetes. Therefore, elevated blood viscosity and hematocrit deserve attention as emerging risk factors for insulin resistance and type 2 diabetes mellitus.

For reducing pain, duloxetine and venlafaxine, pregabalin and oxcarbazepine, tricyclic antidepressants, atypical opioids, and botulinum toxin were more effective than placebo. However, quality of life was poorly reported, studies were short-term, drugs had substantial dropout rates, and opioids have significant risks. Future studies should evaluate longer-term outcomes, use methods and measures recommended by pain organizations, and assess patients' quality of life.

Objectives To summarize the influence of pre-existing diabetes on mortality and morbidity in men with prostate cancer. Methods We searched MEDLINE and EMBASE from inception through October 1, 2008. Search terms were related to diabetes, cancer, and prognosis. Studies were included if they reported an original data analysis of prostate cancer prognosis, compared outcomes between men with and without diabetes, and were in English. Titles, abstracts, and articles were reviewed independently by two authors. Conflicts were settled by consensus or third review. We abstracted data on study design, analytic methods, outcomes, and quality. We summarized mortality and morbidity outcomes qualitatively and conducted a preliminary meta-analysis to quantify the risk of long-term (>3 months), overall mortality. Results 11 articles were included in the review. 1/4 studies found increased prostate-cancer mortality, 1/2 studies found increased non-prostate cancer mortality, and 1/1 study found increased 30-day mortality. Data from 4 studies could be included in a preliminary meta-analysis for long-term, overall mortality and produced a pooled hazard ratio of 1.57 (95% CI: 1.12-2.20). Diabetes was also associated with receiving radiation therapy, complication rates, recurrence, and treatment failure. Conclusions Our analysis suggests that pre-existing diabetes affects the treatment and outcomes of men with prostate cancer.

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Low serum potassium concentrations in African Americans may contribute to their excess risk of type 2 diabetes relative to whites. Whether interventions to increase serum potassium concentrations in African Americans might reduce their excess risk deserves further study. The ARIC Study is registered at clinicaltrials.gov as NCT00005131.

<b>Objective:</b> To determine the longer-term effects of metformin and behavioral weight loss on gut microbiota and SCFAs. <p><b>Methods: </b>We conducted a parallel-arm, randomized trial. We enrolled overweight/obese adults who had been treated for solid tumors but had no ongoing cancer treatment and randomized them (n=121) to: 1) metformin (up to 2000mg), 2) coach-directed behavioral weight loss, or 3) self-directed care (control) for 12 months. We collected stool and serum at baseline (n=114), 6 months (n=109) and 12 months (n=105). From stool, we extracted microbial DNA and conducted amplicon and metagenomic sequencing. We measured SCFAs and other biochemical parameters from fasting serum. </p> <p><b>Results: </b>Of the 121 participants, 79% were female, 46% were black, and the mean age was 60y. Only metformin intervention significantly altered microbiota composition. Compared to control, metformin increased <i>E. Coli</i> and <i>Ruminococcus torques</i> and decreased <i>Intestinibacter Bartletti</i> at both 6 and 12 months, and decreased the genus <i>Roseburia (genus)</i>, including <i>R. faecis</i> and <i>R. intestinalis,</i> at 12 months. Effects were similar when comparing metformin to the behavioral weight loss group. Metformin also altered 62 metagenomic functional pathways and increased butyrate, acetate, and valerate at 6 months. Behavioral weight loss vs. control did not significantly alter microbiota composition, but did increase acetate at 6 months. Increases in acetate were associated with decreases in fasting insulin.</p> <p><b>Conclusions:</b> Metformin, but not behavioral weight loss, impacted gut microbiota composition and function at 6 months and 12 months. Both metformin and behavioral weight loss altered 6-month SCFAs, including increasing acetate which correlated with improved insulin sensitivity.</p>